An interventional study of Artificial intelligence-supported digital nudging in Ultra-Processed Food Consumption, Obesity Prevention and Dietary Behaviour, sponsored by Istanbul Gelisim University. Not yet recruiting. Open to participants aged 12 Years to 25 Years, including healthy volunteers. Per ClinicalTrials.gov, last updated 2026-04-07.
Sponsored by Istanbul Gelisim University · Not applicable, Interventional, and Prevention
This study aims to evaluate the effectiveness of an artificial intelligence (AI)-supported, context-aware digital nudging intervention designed to reduce ultra-processed food consumption and improve dietary sustainability among adolescents and young adults. The intervention utilizes real-time behavioral data, including image-assisted dietary logging and contextual information, to identify high-risk consumption moments and deliver personalized, non-coercive nudges. The study will assess changes in ultra-processed food intake, contextual consumption patterns, and sustainability-related dietary indicators.
This study investigates the effectiveness of an artificial intelligence (AI)-supported, context-aware digital intervention targeting ultra-processed food (UPF) consumption among adolescents and young adults. UPF consumption has been identified as a major contributor to non-communicable diseases and is associated with significant environmental impacts. However, existing digital nutrition interventions largely rely on static, nutrient-based approaches and do not adequately capture real-life behavioral contexts.
The intervention integrates image-assisted dietary logging, contextual data collection (including time, location, and social setting), and explainable artificial intelligence to identify high-risk moments of UPF consumption. Based on these insights, the system delivers adaptive, personalized digital nudges designed to support healthier and more sustainable food choices without restricting user autonomy.
The study follows a controlled evaluation design to assess the effectiveness of the intervention. Primary outcomes include changes in context-specific UPF consumption patterns, while secondary outcomes include overall dietary quality, sustainability-related indicators (such as environmental impact proxies), and user engagement metrics.
This research aims to provide evidence for scalable, ethically governed digital health interventions that integrate behavioral science, nutrition, and sustainability within real-life settings
144 studies on the registry are indexed under Noncommunicable Diseases; 55 are open to participants now.
This study's planned enrollment of 1,000 is above the median of 478 across 95 interventional studies indexed under Noncommunicable Diseases.
Browse Noncommunicable Diseases studies →Istanbul Gelisim University is the lead sponsor of 64 studies on the registry; 8 are open to participants now.
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Exclusion Criteria:
Underlined terms in the criteria open these too. Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
Before you join, the study team explains what taking part involves — its purpose, what happens, the risks and possible benefits — and answers your questions, so you can decide freely. Consent is usually recorded on a form (the informed consent form, ICF) signed by you or, where the law allows, by someone legally authorised to decide for you.
You can keep asking questions during the study, you are told of new information that matters, and you can choose to leave at any time.
Informed consent
Before you join, the study team explains what taking part involves — its purpose, what happens, the risks and possible benefits — and answers your questions, so you can decide freely. Consent is usually recorded on a form (the informed consent form, ICF) signed by you or, where the law allows, by someone legally authorised to decide for you.
You can keep asking questions during the study, you are told of new information that matters, and you can choose to leave at any time.
Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
Participants receive an artificial intelligence (AI)-supported, context-aware digital nudging intervention designed to reduce ultra-processed food (UPF) consumption. The system uses real-time dietary and contextual data to deliver personalized behavioural prompts.
Behavioral: Artificial intelligence-supported digital nudging
Participants have access to the digital platform without active nudging components. No personalized behavioural prompts are delivered.
A context-aware digital intervention delivering personalized nudges based on real-time dietary behavior and contextual data to reduce ultra-processed food consumption.
Change in ultra-processed food consumption (servings per day)
Change in ultra-processed food consumption, expressed as servings per day, assessed using dietary intake data collected via a digital dietary assessment platform (food diary-based tracking system). Consumption will be quantified based on reported frequency and portion size.
Time frame: From baseline to 10 months and 20 months
Change in frequency of ultra-processed food consumption (times per day)
Change in the frequency of ultra-processed food consumption, expressed as times per day, assessed using a digital dietary tracking platform (food diary-based system).
Time frame: From baseline to 10 months and 20 months
Change in proportion of ultra-processed food consumption (% of total intake)
Change in the proportion of ultra-processed food consumption, expressed as percentage of total dietary intake, derived from dietary tracking data collected via a digital dietary assessment platform.
Time frame: From baseline to 10 months and 20 months
Change in temporal eating patterns (eating occasions per day and timing)
Change in temporal eating patterns, including number of eating occasions per day and timing of meals, assessed using time-stamped dietary records collected via a digital dietary tracking platform.
Time frame: From baseline to 10 months and 20 months
Change in context-specific dietary behaviours (categorical variables)
Change in context-specific dietary behaviours, including eating location and social context, assessed as categorical variables using data recorded via a digital dietary tracking platform.
Time frame: From baseline to 10 months and 20 months
No study locations are listed for this record.
Plan to share: No
No publications or documents are linked to this record.
This study is not yet recruiting, as verified in Mar 2026. You cannot join it, but the record below documents what was studied.
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Istanbul Gelisim University